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ObjectivesThis study aims to describe the prevalence of non-communicable disease (NCD) risk factors among the urban poor in Bangladesh.DesignWe conducted a community-based cross-sectional epidemiological study.SettingThe study was conducted in a shantytown in the city of Dhaka. There were 8604 households with 34 170 residents in the community. Those households were categorised into two wealth strata based on the housing structure.ParticipantsThe study targeted residents aged 18–64 years. A total of 2986 eligible households with one eligible individual were selected by simple random sampling stratified by household wealth status. A total of 2551 residents completed the questionnaire survey, and 2009 participated in the subsequent physical and biochemical measurements.Outcome measuresA modified WHO survey instrument was used for assessing behavioural risk factors and physical and biochemical measurements, including glycated haemoglobin (HbA1c). The prevalence of NCD risk factors, such as tobacco use, fruit and vegetable intake, overweight/obesity, hypertension, diabetes (HbA1c ≥6.5%) and dyslipidaemia, was described according to household wealth status and gender differences.ResultsThe prevalence of current tobacco use was 60.4% in men and 23.5% in women. Most of them (90.8%) consumed more than 1 serving of fruits and vegetables per day; however, only 2.1% consumed more than 5 servings. Overweight/obesity was more common in women (39.2%) than in men (18.9%), while underweight was more common in men (21.0%) than in women (7.1%). The prevalence of hypertension was 18.6% in men and 20.7% in women. The prevalence of diabetes was 15.6% in men and 22.5% in women, which was much higher than the estimated national prevalence (7%). The prevalence of raised total cholesterol (≥190 mg/dL) was 25.7% in men and 34.0% in women.ConclusionThe study identified that tobacco use, both overweight and underweight, diabetes, hypertension and dyslipidaemia were prevalent among the urban poor in Bangladesh.

Background Anticipating an initial shortage of vaccines for COVID-19, the Centers for Disease Control (CDC) in the United States developed priority vaccine allocations for specific demographic groups in the population. This study evaluates the performance of the CDC vaccine allocation strategy with respect to multiple potentially competing vaccination goals (minimizing mortality, cases, infections, and years of life lost (YLL)), under the same framework as the CDC allocation: four priority vaccination groups and population demographics stratified by age, comorbidities, occupation and living condition (congested or non-congested). Methods and findings We developed a compartmental disease model that incorporates key elements of the current pandemic including age-varying susceptibility to infection, age-varying clinical fraction, an active case-count dependent social distancing level, and time-varying infectivity (accounting for the emergence of more infectious virus strains). The CDC allocation strategy is compared to all other possibly optimal allocations that stagger vaccine roll-out in up to four phases (17.5 million strategies). The CDC allocation strategy performed well in all vaccination goals but never optimally. Under the developed model, the CDC allocation deviated from the optimal allocations by small amounts, with 0.19% more deaths, 4.0% more cases, 4.07% more infections, and 0.97% higher YLL, than the respective optimal strategies. The CDC decision to not prioritize the vaccination of individuals under the age of 16 was optimal, as was the prioritization of health-care workers and other essential workers over non-essential workers. Finally, a higher prioritization of individuals with comorbidities in all age groups improved outcomes compared to the CDC allocation. Conclusion The developed approach can be used to inform the design of future vaccine allocation strategies in the United States, or adapted for use by other countries seeking to optimize the effectiveness of their vaccine allocation strategies.

The cost of paratuberculosis to dairy herds, through decreased milk production, early culling, and poor reproductive performance, has been well-studied. The benefit of control programs, however, has been debated. A recent stochastic compartmental model for paratuberculosis transmission in US dairy herds was modified to predict herd net present value (NPV) over 25 years in herds of 100 and 1000 dairy cattle with endemic paratuberculosis at initial prevalence of 10% and 20%. Control programs were designed by combining 5 tests (none, fecal culture, ELISA, PCR, or calf testing), 3 test-related culling strategies (all test-positive, high-positive, or repeated positive), 2 test frequencies (annual and biannual), 3 hygiene levels (standard, moderate, or improved), and 2 cessation decisions (testing ceased after 5 negative whole-herd tests or testing continued). Stochastic dominance was determined for each herd scenario; no control program was fully dominant for maximizing herd NPV in any scenario. Use of the ELISA test was generally preferred in all scenarios, but no paratuberculosis control was highly preferred for the small herd with 10% initial prevalence and was frequently preferred in other herd scenarios. Based on their effect on paratuberculosis alone, hygiene improvements were not found to be as cost-effective as test-and-cull strategies in most circumstances. Global sensitivity analysis found that economic parameters, such as the price of milk, had more influence on NPV than control program-related parameters. We conclude that paratuberculosis control can be cost effective, and multiple control programs can be applied for equivalent economic results.